Natural language and machine translation

[ИАД, весна 2026] Математические методы анализа текстов. Лекция 10: IR, RAG

[IAD, Spring 2026] Mathematical Methods of Text Analysis. Lecture 10: IR, RAG

Generative AI L5: Tokenization (Word piece, unigram tokenization), language related terminologies

Generative AI L4: Types of tokenization (word level, character level, subword level), BPE algorithm

Mikhail Gromov - 3/4 Generation, Transformation, Transmission, Memorization, Storage and (...)

Generative AI L2: Evolution of Natural Language Processing

Stanford CS336 Language Modeling from Scratch | Spring 2026 | Lecture 1: Overview, Tokenization

This One Plugin Just 10x’d Claude Code

Why You're Still Better Than AI at Editing Documents - CS50 Tech Talk

“Cross-lingual Transfer for Machine Translation” - Nate Robinson

“LLM-powered exploratory text analysis at scale” - Mian Zhong

NotebookLM trouve les sources, Claude fait le travail — voici comment les connecter

NotebookLM finds the sources, Claude does the work — here's how to connect them

Leveraging Large Speech Language Models as Evaluators for Expressive Speech - Bismarck Odoom

RAG + Gemini en 2026 (TUTO)🔥

RAG + Gemini in 2026 (TUTORIAL)🔥

Language AI in the Space Sciences: Day 4 - Session 7 - March 12, 2026

Language AI in the Space Sciences: Day 3 - Session 5 - March 11, 2026

Language AI in the Space Sciences: Day 3 - Session 4 - March 11, 2026

Language AI in the Space Sciences: Day 2 - Session 2 - March 10, 2026

Language AI in the Space Sciences: Day 2 - Session 1 - March 10, 2026

Lisa Miracci Lunchtime Talk What you Think Matters Semantic Embedding, Computational Explanation,

[ИАД, весна 2026] Математические методы анализа текстов. Лекция 4: Transfer Learning, BERT-like, LLM

[IAD, Spring 2026] Mathematical Methods for Text Analysis. Lecture 4: Transfer Learning, BERT-like, LLM

Машинное обучение и семантический анализ

Machine learning and semantic analysis

Philipp Koehn: Multilingual Language Processing in 21 century: Lessons Learned and Challenges Ahead

Dictez dans Gmail, Word, Slack, courrier & Rapport ! — Speakly AI (par Genspark)

Dictate in Gmail, Word, Slack, Mail & Reports! — Speakly AI (by Genspark)

S3 #44 How should machines translate sensitive language? Brain-to-brain with Sabrina Frohn.

How Attackers Bypass AI Guardrails with Natural Language

Hands-on Machine Learning -- Sequences and NLP with RNNs and Attention

[Generative AI in Urdu/Hindi] Lecture 6: Embeddings – Word formations, ambiguity, vectorization

Elevenlabs just got wrecked. This free AI text to speech is WILD!

[Generative AI in Urdu/Hindi] Lecture 5: Tokenization (cont.) – algorithms, examples, best practices

[Generative AI in Urdu/Hindi] Lecture 4: Tokenization – concept, types, their problems, solutions

[Generative AI in Urdu/Hindi] Lecture 3: Language - embeddings to encoding, modelling to fine-tuning

AI en Retail y CPG, Competencia entre agentes evolutivos, DroPE y RLMs para contextos grandes

AI in Retail and CPG, Competition among evolutionary agents, DroPE and RLMs for long contexts

I Built a Voice Agent That Calls Every New Lead (n8n + Vapi)

[Generative AI in Urdu/Hindi] Lecture 2: Language – concepts to terminologies, vectors to embeddings

8: Deep Learning for Natural Language – Transformers, Self-Supervised Learning

6: Deep Learning for Natural Language – Embeddings

5: Deep Learning for Natural Language – The Basics

Unlock GLM 4.7 & MiniMax M2.1 - Active Expert Control for SPEED or IQ

Google Webinar | Risk Classification with LLMs

Regina Barzilay: Learning to Model Text Structure